| 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | TOTAL | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BACCHUS | 0 | 0 | 0 | 0 | 40 | 38 | 40 | 40 | 38 | 38 | 38 | 272 |
| BIOMHE | 0 | 0 | 0 | 0 | 0 | 0 | 40 | 0 | 0 | 0 | 0 | 40 |
| BISCO | 0 | 0 | 0 | 27 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 27 |
| DIVAG | 0 | 0 | 0 | 0 | 0 | 40 | 0 | 0 | 0 | 0 | 0 | 40 |
| DURUM_MIX_GM | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
| FRAMEwork_BVD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 36 | 0 | 0 | 0 | 36 |
| LepiBats | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50 | 0 | 0 | 0 | 50 |
| MUESLI | 0 | 0 | 60 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 60 |
| OSCAR | 0 | 0 | 0 | 0 | 15 | 33 | 38 | 67 | 88 | 100 | 107 | 448 |
| SEBIOPAG_BVD | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 20 | 20 | 0 | 0 | 60 |
| SEBIOPAG_Plaine de Dijon | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 220 |
| SEBIOPAG_VcG | 19 | 19 | 17 | 17 | 17 | 17 | 17 | 17 | 17 | 17 | 0 | 174 |
| SEBIOPAG_ZAAr | 20 | 20 | 20 | 0 | 20 | 0 | 0 | 20 | 0 | 20 | 0 | 120 |
| SERIPAGE | 0 | 0 | 9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 |
| TOTAL | 59 | 59 | 126 | 65 | 113 | 148 | 175 | 270 | 183 | 195 | 165 | 1558 |
Calculation of diversification indicators and other covariates
Summary
| Indicator | Data | Format |
|---|---|---|
| perimeter and area of the field | RPG | vectoriel |
| mean field size within buffer | RPG | vectoriel |
| hedgerows length around field | RPG + BD haies | vectoriel |
| crop rotation (N-5:N) | RPG + OSO | raster |
| % land cover within buffer | RPG + OSO | raster |
| density of bordures | RPG + OSO | raster |
Data description:
- Registre Parcellaire Graphique (RPG)(45Gb): annual field crop data for the period 2007-2023 available at France scale on IGN website: https://geoservices.ign.fr/rpg. Definition of field (parcelles) are coherent only in the recent period 2015-2023.
- Carte d’occupation des sols du CES OSO – THEIA (OSO)(6.6Gb): annual land cover data for the period 2016-2024. Available for France in raster format and 10m resolution https://doi.org/10.57745/UZ2NJ7. Official access through the CNES website https://geodes-portal.cnes.fr.
- BD Haies v2 (6.8Gb): hedgerows dataset for France available on the IGN website: https://geoservices.ign.fr/bdhaie. BD Haie v2 was produced from satellite images of 2020-2022 (which is a better fit to our data than v1 from images of 2011-2014).
Field observations
Because of data availability (RPG is not released yet for 2024 and OSO is not available before 2016), we will only focus on the period 2016-2023. There were 1275 observations made between 2016 and 2023.
Indicators from vector datasets
Identification of the crop field in RPG
| Nobs | in_RPG | Perc | |
|---|---|---|---|
| BACCHUS | 234 | 189 | 80.77 |
| BIOMHE | 40 | 39 | 97.50 |
| BISCO | 27 | 26 | 96.30 |
| DIVAG | 40 | 40 | 100.00 |
| DURUM_MIX_GM | 2 | 0 | 0.00 |
| FRAMEwork_BVD | 36 | 30 | 83.33 |
| LepiBats | 50 | 30 | 60.00 |
| MUESLI | 60 | 31 | 51.67 |
| OSCAR | 341 | 312 | 91.50 |
| SEBIOPAG_BVD | 60 | 51 | 85.00 |
| SEBIOPAG_Plaine de Dijon | 160 | 160 | 100.00 |
| SEBIOPAG_VcG | 136 | 48 | 35.29 |
| SEBIOPAG_ZAAr | 80 | 80 | 100.00 |
| SERIPAGE | 9 | 9 | 100.00 |
In total, 82 % of the fields observations are covered by RPG data. There are large disparities among projects with SEBIOPAG_VcG, MUESLI and LepiBats having a lower coverage than 60%. The project DURUM_MIX_GM has only one coordinates leading to the entrance of the Institut Agro-Montpellier.
To be discussed:
Some coordinates were taken at the edge or on the boundary of the field, so it is not possible to clearly identify the field. In such case, should we consider the closest field within a distance threshold (e.g. 10m)?
Field size
| BACCHUS | BIOMHE | BISCO | DIVAG | FRAMEwork_BVD | LepiBats | MUESLI | OSCAR | SEBIOPAG_BVD | SEBIOPAG_Plaine de Dijon | SEBIOPAG_VcG | SEBIOPAG_ZAAr | SERIPAGE | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min. | 0.26 | 0.68 | 0.50 | 0.97 | 0.36 | 1.40 | 0.41 | 0.23 | 0.36 | 0.53 | 0.19 | 1.21 | 1.55 |
| 1st Qu. | 0.98 | 1.59 | 1.10 | 2.21 | 0.56 | 2.77 | 1.91 | 0.48 | 0.83 | 5.11 | 1.82 | 2.96 | 2.19 |
| Median | 2.38 | 3.69 | 1.71 | 2.98 | 1.36 | 6.18 | 4.10 | 1.10 | 3.68 | 6.83 | 4.16 | 4.31 | 3.51 |
| Mean | 4.52 | 4.48 | 3.22 | 3.17 | 3.83 | 11.89 | 5.64 | 1.71 | 5.70 | 7.41 | 6.40 | 4.83 | 4.04 |
| 3rd Qu. | 6.16 | 6.29 | 3.15 | 4.02 | 5.01 | 13.96 | 7.61 | 1.96 | 5.20 | 8.78 | 9.90 | 6.09 | 5.19 |
| Max. | 39.27 | 13.99 | 23.69 | 6.01 | 18.15 | 55.47 | 34.05 | 15.60 | 29.02 | 17.82 | 18.35 | 16.22 | 7.60 |
| BACCHUS | BIOMHE | BISCO | DIVAG | FRAMEwork_BVD | LepiBats | MUESLI | OSCAR | SEBIOPAG_BVD | SEBIOPAG_Plaine de Dijon | SEBIOPAG_VcG | SEBIOPAG_ZAAr | SERIPAGE | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min. | 0.26 | 0.68 | 0.50 | 0.97 | 0.36 | 1.40 | 0.41 | 0.23 | 0.36 | 0.53 | 0.19 | 1.21 | 1.55 |
| 1st Qu. | 0.98 | 1.59 | 1.10 | 2.21 | 0.56 | 2.77 | 1.91 | 0.48 | 0.83 | 5.11 | 1.82 | 2.96 | 2.19 |
| Median | 2.38 | 3.69 | 1.71 | 2.98 | 1.36 | 6.18 | 4.10 | 1.10 | 3.68 | 6.83 | 4.16 | 4.31 | 3.51 |
| Mean | 4.52 | 4.48 | 3.22 | 3.17 | 3.83 | 11.89 | 5.64 | 1.71 | 5.70 | 7.41 | 6.40 | 4.83 | 4.04 |
| 3rd Qu. | 6.16 | 6.29 | 3.15 | 4.02 | 5.01 | 13.96 | 7.61 | 1.96 | 5.20 | 8.78 | 9.90 | 6.09 | 5.19 |
| Max. | 39.27 | 13.99 | 23.69 | 6.01 | 18.15 | 55.47 | 34.05 | 15.60 | 29.02 | 17.82 | 18.35 | 16.22 | 7.60 |
There is a strong relation between area and perimeter (Figure 3). In median, field size is 2.8 ha and field perimeter is 790m.
Outliers
To be discussed:
Some fields are defined as Bordure de champ which are not field but borders (as in Figure 5). Should we remove fields from RPG that are not agricultural before running the calculations?
Hedgerows length
Using the field as defined by RPG, we can calculate the length of hedgerows from BD Haies that intersect the field (+ a small buffer).
| B_0m | B_5m | B_10m | |
|---|---|---|---|
| Min. | 0.00 | 0.00 | 0.00 |
| 1st Qu. | 0.00 | 0.00 | 0.00 |
| Median | 0.00 | 30.97 | 68.36 |
| Mean | 82.00 | 167.59 | 213.70 |
| 3rd Qu. | 51.00 | 201.30 | 288.28 |
| Max. | 2935.23 | 4336.95 | 5105.47 |
| NA’s | 230.00 | 230.00 | 230.00 |
| PercWithHedges | 42.11 | 60.00 | 70.14 |
The 230 NA’s correspond to the observations from which no corresponding fields were found. Without buffer, 42% of fields have hedgerows within the field. This percentage increases up to 70% if we consider a 10m buffer around the field.
Outliers
To be discussed:
- Which buffer size should we use to calculate the hedgerows lengths? Without buffer, it might be too restrictive, but is 10m to large, or not enough?
- Should we consider the position of the field sampling when calculating the hedgerows length?
Field size within buffer
| B_500m | B_1000m | B_1500m | |
|---|---|---|---|
| Min. | 0.22 | 0.26 | 0.30 |
| 1st Qu. | 1.50 | 1.57 | 1.55 |
| Median | 2.44 | 2.33 | 2.30 |
| Mean | 3.00 | 2.63 | 2.51 |
| 3rd Qu. | 3.69 | 3.15 | 2.93 |
| Max. | 22.25 | 11.82 | 12.61 |
| NA’s | 13.00 | 7.00 | 5.00 |
We see that some observations don’t have crop field within 500m (N=13). To be checked whether those observations (listed in Table 7) were really made close to an agricultural field.
| Study_ID | Site | Year | |
|---|---|---|---|
| 154 | DURUM_MIX_GM | DIASCOPE | 2017 |
| 232 | DURUM_MIX_GM | DIASCOPE | 2018 |
| 704 | LepiBats | C01 | 2021 |
| 705 | LepiBats | C02 | 2021 |
| 706 | LepiBats | C03 | 2021 |
| 707 | LepiBats | C04 | 2021 |
| 708 | LepiBats | C05 | 2021 |
| 709 | LepiBats | C06 | 2021 |
| 710 | LepiBats | C07 | 2021 |
| 712 | LepiBats | C09 | 2021 |
| 713 | LepiBats | C10 | 2021 |
| 242 | OSCAR | 33_2011_00002 | 2018 |
| 1133 | OSCAR | 11_2023_00004 | 2023 |
Outliers
Summary and questions about vector indicators:
- Most observations fit within RPG dataset (Table 2).
- But some coordinates were taken at the very edges of field (Figure 2), so we might need to identify the closest field instead (and add a distance threshold, e.g. 10m).
- Adding the RPG complété require more data processing, and in any case it won’t cover all observations (but it will complete some wineyards). The RPG classes might also be less consistent within our timeframe and would require to be further checks.
- We might need to exclude some fields from RPG (e.g. Bordure, Bande tampon, Culture sous serre, Bois paturés, Surface non agricole, Truffière) to only includes crop fields that are relevant for us.
- The position of the observations within the field might influence the results (influence of hedgerows, or of agricultural practices). We might want to add an indicator reflecting the distance to the center of the field and/or the distance to the closest field boundary?
Indicators from raster datasets (RPG+OSO)
Crop rotation (N-5:N)
| inRPG | inOSO | NAs | |
|---|---|---|---|
| lulc_N | 1042 | 233 | 283 |
| lulc_N-1 | 1100 | 214 | 244 |
| lulc_N-2 | 1028 | 221 | 309 |
| lulc_N-3 | 923 | 213 | 422 |
| lulc_N-4 | 779 | 209 | 570 |
| lulc_N-5 | 632 | 181 | 745 |
| landcover class | N |
|---|---|
| RPG_Vigne (sauf vigne rouge) | 484 |
| RPG_Blé tendre d’hiver | 165 |
| RPG_Autre verger (y compris verger DOM) | 79 |
| OSO_Vignes | 64 |
| OSO_Forêts de feuillus | 41 |
| OSO_Prairies | 41 |
| RPG_Maïs (hors maïs doux) | 34 |
| RPG_Orge d’hiver | 29 |
| RPG_Maïs ensilage | 26 |
| RPG_Mélange de céréales ou pseudo-céréales d’hiver entre elles | 25 |
| RPG_Vigne : raisins de cuve non en production | 24 |
| RPG_Colza d’hiver | 21 |
There are 648 observations with complete time series from year N to N-5. From these observations with complete rotation information, 342 have the same crop group for the whole time period, while 74 fields have four different crop groups in the past 6 years.
| BACCHUS | FRAMEwork BVD |
LepiBats | OSCAR | SEBIOPAG BVD |
SEBIOPAG Plaine de Dijon |
SEBIOPAG VcG |
SEBIOPAG ZAAr |
|
|---|---|---|---|---|---|---|---|---|
| 1 | 116 | 28 | 39 | 119 | 35 | 3 | 2 | 0 |
| 2 | 0 | 7 | 8 | 71 | 4 | 6 | 9 | 19 |
| 3 | 0 | 1 | 3 | 46 | 1 | 16 | 17 | 12 |
| 4 | 0 | 0 | 0 | 18 | 0 | 29 | 19 | 8 |
| 5 | 0 | 0 | 0 | 1 | 0 | 6 | 4 | 1 |
FALSE TRUE <NA>
33 1012 513
Land cover within buffer
| buffer_500 | buffer_1000 | buffer_1500 | |
|---|---|---|---|
| n_classes | 186 | 220 | 237 |
| av_perc_rpg | 50 | 47 | 45 |
Density of bordures
To be defined.
Summary and questions about vector indicators:
- There are up to
237land cover in the RPG+OSO dataset. Here we simplified it using the Référentiel des cultures as an illustration. Before the extracted information can be usefull in the project, it requires further work on land cover class homogeneization. - The edge density needs further thinking.